Vpx-Independent Lentiviral Transduction and shRNA-Mediated Protein Knock-Down in Monocyte-Derived Dendritic Cells
Bibliographic record
Abstract
The function of dendritic cells (DCs) in the immune system is based on their ability to sense and present foreign antigens. Powerful tools to research DC function and to apply in cell-based immunotherapy are either silencing or overexpression of genes achieved by lentiviral transduction. To date, efficient lentiviral transduction of DCs or their monocyte derived counterparts (MDDCs) required high multiplicity of infection (MOI) or the exposure to the HIV-2/SIV protein Vpx to degrade viral restriction factor SAM domain and HD domain-containing protein 1 (SAMHD1). Here we present a Vpx-independent method for efficient (>95%) transduction of MDDCs at lower MOI. The protocol can be used both for ectopic gene expression and knock-down. Introducing shRNA targeting viral entry receptor CD4 and restriction factor SAMHD1 into MDDCs resulted in down-regulation of targeted proteins and, consequently, expected impact on HIV infection. This protocol for MDDCs transduction is robust and free of the potential risk arising from the use of Vpx which creates a virus infection-prone environment, potentially dangerous in clinical setting.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".